DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-20 were previously pending and subject to a final office action mailed 03/25/2025. Claims 1-3, 11-12, 17-18, and 20 were amended; no claim was cancelled, or added in a reply filed 09/24/2025. Therefore claims 1-20 are currently pending and subject to the non-final office action below.
Response to Arguments
Applicant's arguments filed 09/24/2025 in regards to section 101 arguments have been fully considered but they are not persuasive.
Applicant argues that the claim is not directed to an abstract idea because it involves “restricting a database based on descriptive artifacts derived from free form content” (remarks p. 9-10). Examiner respectfully disagrees.
Examiner respectfully disagrees. Under the Mayo/Alice framework, claims must be evaluated at an appropriate level of abstraction, looking to the claim as a whole and the character of the claimed advance over the prior art.
The claim remains directed to organizing human activity because even with amendments, claim 1 fundamentally recites: receiving a hospitality booking request, deriving descriptive artifacts from the request, matching facilities to the request using scoring, storing unmatched features, restructuring database based on unmatched features, delivering matching facility to users. The claim’s character is still about matching user booking requests to hospitality facilities. The database restructuring is merely ancillary step within the overall abstract concept of matching users to services. Therefore, per the 2019 Revised patent subject matter eligibly guidance of 2019, the claims fall under commercial interactions because the booking reservations is a commercial interactions, managing personal behavior/interactions because of the matching of user preferences to facilities and fundamental economic practice because of the matching of facilities to user request.
Moreover, Applicant characterizes the claim as being “about” database restructuring, but this mischaracterizes the claim scope. The “restructuring” limitation is one step among many in a broader method of booking/matching. Courts look to the claim as a whole, not isolated limitation in a vacuum (please see TLI Communications v. AV automative 823 F.3D 607 (Fed. Cir. 2016) “classifying and storing data in a database based on content does not transform an otherwise abstract idea into an invention).
The claims also recite a mental process because certain limitations such as receiving a booking request, deriving features from the request, matching request to facilities (using judgment), noting which features do not match, modifying the booking system and telling the customer about the matching facility are steps that can be done in the human mind (with the help of pen and paper).
Applicant argues that the claim is integrated into a practical application because it restructures a database and increases efficiency of booking systems (remarks p. 10).
Examiner respectfully disagrees. Examiner finds that the claim is not integrated into a practical application under the revised PEG because the claimed limitations do not provide a technological improvement or apply the abstract idea in a non-conventional, specific manner. The database restructuring is a generic computer functionality. The claim broadly recites “restricting the hospitality/tourism feature database to include at least one new field”. This is functional claiming at a high level of abstraction. The claim does not specify what database architecture is used, what restricting algorithm or process is employed or what makes the restructuring non-conventional or improved.
Per the PEG, a claim is not integrated into a practical application when it merely uses a computer as a tool to perform an abstract idea. “Restructuring a database” is a generic database operation, adding fields to database schemas is routine and conventional database management (please see MPEP 2106.05(f)).
Applicant argues the claim provides an “improvement” that “increases efficiency” but this is conclusory and unsupported. Per MPEP 2106.05(a), to qualify as an improvement to technology, the specification must: describe a technical problem, explain now the claimed invention solves that problem and demonstrate the improvement is in computer functionality and not just use of computers.
Here, Applicant’s “improvement” is merely using a database more effectively for booking – this is an improvement to the business process of booking, not an improvement to database technology (compare with Enfish v. Microsoft 822 F.3d 1327, where the court found patent eligible a specific self-referential database structure that improved database performance with measurable technical benefits (faster searching, smaller memory footprint)).
Here, the specification does not provide evidence of reduced memory usage, faster query processing, novel database architecture or technical benchmarks or measurements. Instead, the improvement is that the booking process becomes more user friendly by learning from past searches. This is an improvement to the user experience and not computer technology.
Moreover, leveraging free form content conflates what the invention does which is a business objective with how it does it which is a technical implementation. Making a booking system “more powerful” is a business goal, not a technical improvement to computers.
Finally, contrary to Applicant’s argument, the claims limitations, alone or in combination do not provide significantly more. Examiner finds the claim lacks an inventive concept that transforms the claim into patent eligible subject matter under step 2B. The ordered combination of input, parsing, matching, storing unmatched, update database and output is predictable and conventional sequence of database operations. There is no unexpected synergy, unconventional arrangement, or technical innovation in the combination. Therefore, the claims are not patent eligible.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 1/21 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “receiving a request for a hospitality booking from a requesting user, said request including free-form content; deriving, from the free-form content, a plurality of descriptive artifacts related to an intended utility of the requested booking; determining a matching facility from a hospitality/tourism feature [ledger] based on a scoring algorithm, the matching facility matching at least some features of the request storing unmatched features of the request in an unmatched data store; restructuring the hospitality/tourism feature [ledger] to include at least one new field in association with said matching facility, the at least one new field reflecting usability of said matching facility for the intended utility related to said descriptive artifacts as an alternative to one or more of the unmatched features of the request said processor generating for delivery to said requesting UCD said determined matching facility for selection; and further restructuring the hospitality/tourism feature [ledger] to include the at least one new field in association with at least one other facility”
The limitations above, is a process that, under its broadest reasonable interpretation, covers determining and delivering a lodging facility matching a user request which is a method of organizing a human activity and mental process. That is, the method allows for fundamental economic principles or practices; commercial interactions (including advertising, marketing or sales activities or behaviors; business relations) and managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) and capable of being performed in the human mind.
This judicial exception is not integrated into a practical application. In particular, the claim recites computing device (UCD) with a user-controlled graphical user interface (GUI), processor, at least one data store, a hospitality/tourism feature database and unmatched data store and (one or more non-transitory computer readable media. Each of the additional limitations is recited at a high level of generality which is no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, alone or in combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are nothing more than mere instructions to apply the exception on a general computer (“saving data in a memory and electronic record keeping is a well-understood, routine and conventional activity” (please see MPEP 2106.05(d)(II)))
Dependent claim 2 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application (local and remote data store is recited at a high level of generality which amounts to instructions of applying the abstract idea in a computer) or providing significantly more limitations (receiving and transmitting data over a network, saving and retrieving data in a memory and electronic ledgers are well understood, routine and conventional functions according to MPEP 2106.05(d)(II)).
Dependent claim 3 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitations.
Dependent claim 4 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitations.
Dependent claim 5 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application (remote data store is recited at a high level of generality which amounts to instructions of applying the abstract idea in a computer) or providing significantly more limitations.
Dependent claim 6 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitations.
Dependent claim 7 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitations.
Dependent claim 8 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitations.
Dependent claim 9 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitations.
Dependent claim 10 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 1 without successfully integrating the exception into a practical application or providing significantly more limitations.
Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “receive a request for a hospitality booking from a requesting user and to derive, from free-form content included in the request, a plurality of descriptive artifacts related to an intended utility of the requested booking; determine at least one matching facility from at least one [ledger] based on a scoring algorithm, said matching facility matching at least some features of the request, and to store unmatched features of the request; restructure the at least one data store to include at least one new descriptive field in association with said matching facility, the at least one new field reflecting usability of said matching facility for the intended utility related to said descriptive artifacts as an alternative to one or more of the unmatched features of the request; generate for delivery said determined matching facility for selection and to restructure the at least one data [ledger] to include the at least one new field in association with at least one other facility”
The limitations above, is a process that, under its broadest reasonable interpretation, covers determining and delivering a lodging facility matching a user request which is a method of organizing a human activity and mental process. That is, the method allows for fundamental economic principles or practices; commercial interactions (including advertising, marketing or sales activities or behaviors; business relations) and managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) and concepts that can be done in the human mind.
This judicial exception is not integrated into a practical application. In particular, the claim recites a processor, a communication interface, at least one data store, a graphical user interface (GUI) on a requesting user computing device (UCD) and hospitality/tourism feature database. Each of the additional limitations is recited at a high level of generality which is no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, alone or in combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements are nothing more than mere instructions to apply the exception on a general computer.
Dependent claim 12 is also directed to an abstract idea without significantly more because it further narrows the abstract idea described in relation to claim 11 without successfully integrating the exception into a practical application or providing significantly more limitations.
Dependent claim 13-20 are also directed to an abstract idea without significantly more because they further narrow the abstract idea described in relation to claim 11 without successfully integrating the exception into a practical application (at least one remote data store (claim 15) and a data store (claim 18) are still recited at a high level of generality which amounts to instructions of applying the abstract idea on a computer) or providing significantly more limitations.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 3, 11, 12, 20, and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Elworthy (US 7389224) in view of Grabowski (US 7698254) and LeClair (US 20080052297).
As per claim 1/11/21, Elworthy discloses a system/a computer program product/method for a processor to adapt search input criteria for searching at least one data store while fulfilling a hospitality booking request the method comprising (Examiner notes that hospitality booking is a field of use limitation which does not get patentable weight because it does not how the algorithm functions. Database search methods are domain agnostic):
receiving a request for a hospitality booking from a requesting user computing device (UCD) with a user-controlled graphical user interface (GUI), said request including free-form content (4:25-45, “10) A parser 2 is provided for receiving the input query from the query input device 1a to generate semantic and syntactic information. The parser 2 also parses information from a database 3 which is to be searched. The parser 2 thus generates two sets of parsed data which is passed to a matching engine 4 to match the parsed data. The matching engine 4 in this embodiment performs matching using both semantic and syntactic information from the parser 2. The use of the semantic and syntactic information provides a more accurate matching technique.” Claim 1, “receiving an input query in the form of units of the natural language and outputting a result in the form of output data”,);
deriving, from the free-form content, a plurality of descriptive artifacts related to an intended utility of the requested booking (5:20-25, “In step S1 the user inputs a natural language query. This input query is then parsed in step S2. In step S3 a set of reference data in the database to be searched is selected and parsed. The parser in this embodiment comprises a finite state parser carrying out a dependency parsing operation.…claim 1, “searching for and identifying any matches between the units of the input query and units of the data using reference data from said database so as to identify matched units”, 4:35-42, “A context generating engine 5 generates context data for the matched data in accordance with the linguistic relationship data. A context gathering engine 7 receives the context data and uses this to generate a hierarchical index structure.”);
storing unmatched features of the request in an unmatched data store (6:12-23, “If in step S12 it is determined that the unmatched word u is at the end of a path from a matched word t as defined in the path rules, in step S14 it is determined whether the unmatched word u is present in a valid phrase defined in the valid phrase rule. If there is no valid phrase, in step S13 the next unmatched word u is selected and the process returns to step S12. If a valid phrase is identified the smallest valid phrase containing the word u is determined in step S15 and in step S16 the phrase is added to the memory referenced to the matched word t. The memory thus stores the context data as unmatched words or phrases reference or linked to the respective matched words.”);
as an alternative to one or more of the unmatched features of the request said processor generating for delivery to said requesting UCD said determined matching facility for selection (4:47-53, “FIG. 2 illustrates schematically an embodiment of the present invention comprising a multi-purpose computer programmed to implement the present invention. The various components of the computer are illustrated linked by the computer bus 14. A display device 10 is provided for outputting the search results and the context data”);
However, Elworthy does not disclose but Grabowski discloses deriving a plurality of descriptive artifacts related to an intended utility of the requested booking (3:48 -4:31, “The first preliminary step in structuring a search engine is to determine what features the search engine will look for… Features are thus a meta-level description of the sorts of data that will be sought. Those in the art can analyze database content to determine what features will produce the best results in specific instances.”);
determining a matching facility from a hospitality/tourism feature database based on a scoring algorithm, the matching facility matching at least some features of the request (abstract, 6:11-68, “the system develops a rough score for the query, by extracting features from the query, assigning match scores to query features matching database features);
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Grabowski in the teaching of ElWorthy, in order to speed up searching (please see Grabowski 1:50).
However, Elworthy does not disclose but LeClair discloses restructuring the hospitality/tourism feature database to include at least one new field in association with said matching facility, the at least one new field reflecting usability of said matching facility for the intended utility related to said descriptive artifacts (paragraph 4, “enabling the addition by users of attributes and values associated with nodes in the taxonomy database, as well as searching the database to locate records matching specified attribute values.”, “The user indicates that she wishes to extend the database schema and add to the taxonomy, supplying the new attribute and value. Alternatively, the user indicates that she wishes to extend the taxonomy by providing a new value for an already existing attribute”),
further restructuring the hospitality/tourism feature database to include the at least one new field in association with at least one other facility (paragraph 28, “The new attribute and value are received by server 102 and communicated in turn to taxonomy engine 106 at step 906. Also communicated to taxonomy engine 106 is an indication, for example a record ID, of the database record where the schema modification request was initiated--for example, the record a user was viewing when she selected a modification option.”, claim 2, “receiving from a second user a second value for the new attribute; and modifying a composite value for the attribute of the record, the composite value determined based on all received values for the attribute of the record.”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by LeClair in the teaching of ElWorthy, in order to extend the database schema (please see LeClair abstract).
As per claim 3/12, Elworthy discloses wherein at least one of said descriptive artifacts is or is associated with an event space (abstract ,” The query is input in the form of units of the natural language and this is matched with units in the natural language of the data. Where there are unmatched units in the query and/or the data, context data in the form of one or more unmatched units of the query and/or the data is generated.”, when applies to hospitality booking, the “units” or “descriptive artifacts” can describe any type of hospitality facility including hotels, restaurants, conference centers, event venues, meeting spaces, etc).
As per claim 20, Elworthy discloses wherein said processor is further configured to determine the at least one matching facility further based on at least user input in combination with dimensional artifacts in inventory parameters in the at least one data store (abstract, “The query is input in the form of units of the natural language and this is matched with units in the natural language of the data.”, 5:10-13, “ The database 16 is also provided and comprises the database 3 of FIG. 1. This database contains the sets of data to be found by the search.”, 5:20-25, “In step S1 the user inputs a natural language query. This input query is then parsed in step S2. In step S3 a set of reference data in the database to be searched is selected and parsed.” Under BRI, “dimensional artifacts” are structured data attributes/parameters. Elworthy discloses “data units” within a database “record” which are dimensional artifacts – structured attributes defining database entries. “inventory parameters” are database attributes/fields describing available items.)
Claim(s) 2 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Elworthy (US 7389224) in view of Grabowski (US 7698254) and LeClair (US 20080052297), as disclosed in the rejection of claim 1, in further view of Rennison (US 7827125).
As per claim 2, Elworthy does not disclose but Rennison discloses searching a local data store for optional additive features (23:16-35, “A KnowledgeBase API 216 that Stores data in a KnowledgeBase repository; Interfaces with a Rule Processing Engine 204 and a Concept Synonym Matching Engine 206 to identify Concept in text strings; and Updates a network of Concept relationships that are indexed by a Concept Cube 208 that maintains collections of inverted indexes between Concepts and between Concepts and primitive values such as Strings, numbers (e.g. doubles, floats, and integers), Dates, and Geographical Points A Rule Processing Engine 204 that uses a set of concept matching rules to normalize, map, and split input strings into substrings and searches the substrings for concepts. A Concept Synonym Matching Engine 206 to match input strings to Concepts in a KnowledgeBase 108. A Concept Cube 208 that maintains collections of inverted indexes between Concepts.”), determining applicable optional additive features based on a feature scoring algorithm including at least a known correlation between said matching facility and features in a remote data store associated with at least the matching facility or a related facility (34:35-45, “selects a set of matching Concepts and uses a set of fuzzy search algorithms to determine a rank ordering of the matching Concepts based on a score for each matching Concept.”, 47:33-40, “The ScoreCriteria (described above) can use the ScoreEvaluator 740 to compute partial scores. The ScoreEvaluator 740 can define a Target AttributePath that is used to select values that correspond to a Target Concept, and an Evaluator function (as described above) that evaluates the Target Values and computes a partial score. A ScoreCriteria may define one or more ScoreEvaluators for a given ScoreCriteriaValue.”; abstract “Contextual personalized information retrieval uses a set of integrated methodologies that can combine automatic concept extraction/matching from text, a powerful fuzzy search engine, and a collaborative user preference learning engine to provide accurate and personalized search results.”, 17:1-12, “This attribute may store String values that define patterns that are used by the Concept Synonym Matching Engine to find Concepts input Strings A ParentAttribute (optional)--Defines the parent(s) Concept(s). Instances of this Attribute are used to form a hierarchy or directed acyclic graph of relationships within a Category A ChildAttribute (optional)--Defines the children Concepts. Instances of this Attribute are used to form a hierarchy or directed acyclic graph of relationships within a Category. This ConceptAttribute is the converse ConceptAttribute of the ParentAttribute.” The “known correlation” in the claim corresponds to the concept relationships and hierarchies taught by Rennison, where concepts (corresponds to “features”) are related through parent child and hierarchical relationships); and delivering said applicable optional additive features to said GUI (33:55-61, “A Presentation Layer 304 that presents the search results to the user or another process. A Business logic layer 306 for translating users input query into a search.”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Rennison in the teaching of ElWorthy, in order to learn user preferences to construct one or more profiles for producing personalized search results. (please see Rennison abstract).
As per claim 10, Elworthy discloses wherein said matching facility is usable for multiple purposes (As stated in claim 3 rejection, Elworthy discloses searching for hospitality facilities as part of the search engine capabilities. Searching for a hospitality facility is searching for an event space. An event “usable for multiple purpose” is a result-based limitation that describes a characteristic of the facility (the search result), not a functional limitation of the method. Per MPEP 2114, result based limitations that do not specify how the result is achieved may be given little patentable weight. The claim does not specify how the “multiple purposes” characteristic is achieved, identified, or utilized by the method. It merely states that the matched facility has this property, insufficient to distinguish from prior art searching for the same facility types).
Claim(s) 4 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Elworthy (US 7389224) in view of Grabowski (US 7698254) and LeClair (US 20080052297), Rennison (US 7827125), as disclosed in the rejection of claim 2, in further view of Falk (US 8352454).
As per claim 4/14, Elworthy does not disclose but Falk discloses wherein said optional additive features and said matching facility are sourced from different providers (7:16-36, “A primary search provider is a search provider that contains flight information for a large number of airlines and typically provides the majority of the information is response to a search request. In this example, an effort is made to identify at least one primary search provider for each user request received, however, there may be instances where identifying a primary search provider is not possible… A search provider is typically categorized as a secondary search provider if it contains flight information that would not otherwise be available from other search providers.”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Falk in the teaching of Elworthy, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim(s) 5 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Elworthy (US 7389224) in view of Grabowski (US 7698254) and LeClair (US 20080052297), Rennison (US 7827125), as disclosed in the rejection of claim 2, in further view of Chen (US 7,493,261).
As per claim 5/15, Elworthy does not disclose but Chen discloses further comprising determining resource availability and resource pricing for said optional additive features by querying at least one remote data store (abstract, “a server provides access to a plurality of computer reservation systems (CRSs) for a client initiating a travel booking request.”, 8:45-52, “a client of the super PNR TMS server 100 of the invention can transparently make travel bookings using more than one CRS (GDSs and direct connect CRSs) for different travel item segments (e.g. air, car, and hotel) to thereby choose the best travel item to suit their needs (e.g. based on price, corporate relationship with certain vendors, etc.).”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Chen in the teaching of Elworthy, in order to utilizes multiple computer reservation systems (CRSs) for making travel related bookings (Chen, abstract).
Claim(s) 7 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Elworthy (US 7389224) in view of Grabowski (US 7698254) and LeClair (US 20080052297), as disclosed in the rejection of claim 1, in further view of Cooper (US 2014/0324812).
As per claim 7/17, Elworthy discloses storing unmatched features in a local unmatched data store (6:12-23). However, Elworthy does not disclose but Cooper discloses wherein the unmatched features are correlated with at least one descriptive artifact for use in a plurality of facilities (paragraph 73, “In operation 92, the intent management tool 67 identifies logged queries that do not match any current intent categories. One or more new intent categories are then created for the non-matching queries in operation 94. The new intent categories are either manually generated by the administrator or automatically generated by a natural language engine 71 as described above in FIGS. 5A and 5B.”, claim 6, “wherein said processing of the queries that remain unmatched further includes: outputting a request to correlate the first query grouping with one of the existing intent categories or a new intent category; and receiving back an input assigning the first query grouping with a particular one of the existing intent categories or the new intent category”. Examiner respectfully note that “for use in a plurality of facilities” is an intended use limitation with no patentable weight. Additionally, “at least one descriptive artifact” does not have any effect on the structure of database system. The system or the administrator will be able to create any category which is equivalent to “at least one descriptive artifact” to correlate the unmatched queries.).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Cooper in the teaching of Elworthy, in order to identify queries from a plurality of users over a period of time that use different natural language formations to request similar information (Cooper, abstract).
Claim(s) 8-9 and 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Elworthy (US 7389224) in view of Grabowski (US 7698254) and LeClair (US 20080052297), Rennison (US 7827125), as disclosed in the rejection of claim 2, in further view of Naam (US 7562068).
As per claim 8/18, Elworthy does not disclose but Rennison discloses searching for optional additive features and determining applicable features based on scoring (34:35-45, “selects a set of matching Concepts and uses a set of fuzzy search algorithms to determine a rank ordering of the matching Concepts based on a score for each matching Concept.”, 47:33-40, “The ScoreCriteria (described above) can use the ScoreEvaluator 740 to compute partial scores. The ScoreEvaluator 740 can define a Target AttributePath that is used to select values that correspond to a Target Concept, and an Evaluator function (as described above) that evaluates the Target Values and computes a partial score. A ScoreCriteria may define one or more ScoreEvaluators for a given ScoreCriteriaValue.”; abstract “Contextual personalized information retrieval uses a set of integrated methodologies that can combine automatic concept extraction/matching from text, a powerful fuzzy search engine, and a collaborative user preference learning engine to provide accurate and personalized search results.”, 17:1-12, “This attribute may store String values that define patterns that are used by the Concept Synonym Matching Engine to find Concepts input Strings A ParentAttribute (optional)--Defines the parent(s) Concept(s). Instances of this Attribute are used to form a hierarchy or directed acyclic graph of relationships within a Category A ChildAttribute (optional)--Defines the children Concepts. Instances of this Attribute are used to form a hierarchy or directed acyclic graph of relationships within a Category. This ConceptAttribute is the converse ConceptAttribute of the ParentAttribute.” The “known correlation” in the claim corresponds to the concept relationships and hierarchies taught by Rennison, where concepts (corresponds to “features”) are related through parent child and hierarchical relationships); and delivering said applicable optional additive features to said GUI (33:55-61, “A Presentation Layer 304 that presents the search results to the user or another process. A Business logic layer 306 for translating users input query into a search.”).
However, Elworthy in view of Rennison does not disclose but Naam discloses said feature scoring algorithm is further revised based on trend analysis encompassing prior requests (abstract, “The method includes monitoring user selections in response to user receipt of search results and tracking metadata related to user selections for user selections that exhibit a threshold satisfaction level. The method additionally includes storing the tracked metadata as user preferences and adjusting a ranking mechanism to increase the weight of user preferences in order to increase a ranking for search results that exhibit user preferences.”, 5:55-60, “The metadata tracking mechanism 38 identifies statistically abnormal and significant correlations between page attributes and user satisfaction.”, 6:60-65, “when the SST 30 has identified a set of page attributes (such as categories, document type, document length, or other metadata) that, for this user correlate with satisfaction in a way that is substantially and statistically significantly beyond their correlation with user satisfaction for the population as a whole, it will report these correlations and the strength of their deviation from the norm”, 6:24-25, “the ranking mechanism 52 may adjust its ranking algorithm weights based on user satisfaction.”)
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Naam in the teaching of Elworthy in view of Rennison, in order to rank search results based on user preferences (Naam, abstract).
As per claim 9/19, Elworthy in view of Grabowski, LeClair, Rennison, and Naam disclose the limitation of claim 8. Elworthy does not disclose but Naam further discloses wherein said trend analysis is used to determine predictive demand (6:42-47, “the search may be a new non-repeat search. If the user preferences section 32 indicates that the user typically selects documents from ".edu" sites, the SST 30 will pass this information to the PR 50. The PR 50 will increase the weights of the educational results in order to increase their rankings.”, 7:1-6, “From that point on, until the SST 30 reports a change in correlation or the user instructs otherwise, the PR 50 will instruct the core internet search engine 210 to more heavily weigh these page attributes in ranking.”, abstract, “storing the tracked metadata as user preferences and adjusting a ranking mechanism to increase the weight of user preferences in order to increase a ranking for search results that exhibit user preferences.” The system identifies pattern and predicts continuation which is forecasting future demand based on historical trends. The system adjusts before future searches occurs by varying the weight. The system forecasts preference will continue and adjusts for all subsequent searches)(please see claim 8 rejection for combination rationale).
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Elworthy (US 7389224) in view of Grabowski (US 7698254) and LeClair (US 20080052297), as disclosed in the rejection of claim 11, in further view of Altman (US 2003/0120526).
As per claim 13, Elworthy does not disclose but Altman discloses wherein the processor is further configured to deliver an order for at least one optional additive feature to a feature provider (paragraph 12, “receiving request criteria from the traveler; retrieving at least one option that relates to the request criteria by searching multiple data sources at the same time, the multiple data sources comprising: a global distribution system data source, a public Web site, a travel aggregation public Web site, and a data source privately connected to a vendor; displaying the at least one option to the traveler in a common interface regardless of the data source; receiving at least one selection for booking from the at least one option; directing the user to one of the multiple data sources for booking of the at least one selection”).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of the invention to include the limitation above as taught by Altman in the teaching of Elworthy, in order to booking and expensing travel products and services utilizing multiple data sources and presenting information pulled from the multiple data sources in one user-friendly format (Altman, abstract).
Non-Obviousness and Novelty
Claim 6 recites “wherein said resource pricing is calculated based on said request, selected features, and determined fees for preparing applicable features.” No prior art was applied to the claims because the combination will result in a piecemeal rejection.
The closest prior art is Schkolnick (US 5729697). Schkolnick discloses calculate the price based on each object added to the mobile shopping cart. However, it does not disclose a fee to prepare the items. Nevertheless, the combination of schkolnick in view of Elworthy, Grabowski, LeClair, Rennison and Chen would have been non-obvious because it would have resulted in a rejection using hindsight.
Conclusion
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OMAR . ZEROUAL
Examiner
Art Unit 3628
/OMAR ZEROUAL/Primary Examiner, Art Unit 3628